Uncovering Collective Online Learning Habits

Abstract

In this paper, we analyzed the learners’ behavior data of the large-scale online course (MOOC). We used the data of learners’ Learning behavior to establish the learner-video dipartite network. The two sets of the network are the learners and video collections. In this study, we found the pattern that learners watch videos obeys power-law distribution. In order to study the collective online learning habits, we performed a distribution fit on the learner's video behavior and calculate the parameters, and found that learners' online learning behavior obeys the power-law distribution. Based on the above research, we found the collective online learning habits, which provides a theoretical basis for online course builders to master learners' learning habits.